| Laboratory of measurements of environmental parameters and data processing |
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Code
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119391 |
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Language
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ITA |
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Type of certificate
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Competence
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| Module:
(objectives)
Modulo di Sensori, trasduttori, plc e datalogger KNOWLEDGE AND UNDERSTANDING Students will acquire a thorough understanding of the fundamental concepts and technologies in precision agriculture and livestock farming, including sensor systems, microcontrollers, and automation systems. They will understand how digital technologies impact the management of agricultural and livestock activities and the benefits of implementing these technologies. APPLYING KNOWLEDGE AND UNDERSTANDING Students will learn to apply acquired knowledge in practical settings, using sensors and automation systems to improve the efficiency of agricultural and livestock operations. They will be able to design and implement precision agriculture solutions tailored to the specific needs of different production contexts. MAKING JUDGEMENTS Students will develop the ability to critically evaluate available technological solutions, selecting the most appropriate ones to optimize business operations. They will be capable of identifying and managing technical non-conformities within agricultural and livestock systems. COMMUNICATION SKILLS Students will gain communication skills that enable them to present ideas and projects clearly and effectively to colleagues and external stakeholders. They will be able to collaborate with multidisciplinary teams and adapt their communication to different professional contexts. LEARNING SKILLS Students will develop the ability to learn independently, continuously updating themselves on technological innovations in the agricultural and livestock sectors. They will be encouraged to participate in work groups and develop research projects on specific topics, thus fostering active and continuous learning.
Modulo di Elaborazione dati KNOWLEDGE AND UNDERSTANDING The student will acquire the basic knowledge useful for setting up: - plans for the collection of data in the farm, under the field conditions and from available databases (e.g. climate data); - dataset for collecting and organizing data; - the processing of data collected through the use of software (e.g. Excel). APPLYING KNOWLEDGE AND UNDERSTANDING The student will have the opportunity to apply knowledge in a working environment, with an understanding of technical terms and the ability to manage data and interact with other professional figures (Agronomists, Nutritionists, Veterinarians). MAKING JUDGEMENTS The student will have the ability to independently develop their own assessments regarding the collection and management of data and datasets. COMMUNICATION SKILLS Ability to work in a team and relate. LEARNING SKILLS Learning will also be verified through work groups on specific topics.
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Language
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ITA |
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Type of certificate
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Profit certificate
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Credits
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4
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Contact Hours
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32
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Type of Activity
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Teacher
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Colantoni Andrea
(syllabus)
• Generalities and definitions • Elements of physics: pressure, thermodynamic aspects, references to energy balances and heat exchange. • Environmental parameters: physical parameters. • Simulation models for microclimatic parameters • continuous monitoring of external environmental parameters (temperature, pressure, speed; and wind direction, solar radiation) by means of special control units; • monitoring of the microclimate of indoor environments with unmanned control units: from the survey of the main environmental parameters (air temperature, average radiant temperature, air speed, relative humidity, dew temperature, atmospheric pressure, average natural lighting) it is possible to determine the indices of well-being (UNI 7730), such as the expected average grade (PMV) and the value of the expected percentage of dissatisfied (PPD). • Evaluation of environmental parameters for monitoring in severe hot and cold environments (IREQ and PHS). • Air quality monitoring systems in indoor and outdoor environments (carbon dioxide, nitrogen dioxide, sulfur dioxide, formaldehyde, benzene and ozone) • measurements of the concentration of radon gas in indoor environments; • monitoring of polluting emissions (carbon monoxide, sulfur oxides, nitrogen oxides, dust) of heating systems powered by different fuels and the effect on the environment. • Sensors for monitoring environmental parameters and data acquisition and processing: data loggers and PLCs and transducers. • Man-machine interconnected systems for the livestock sector. • Practise
(reference books)
Lecture notes and lecture notes (available online).
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Dates of beginning and end of teaching activities
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From to |
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Delivery mode
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Traditional
At a distance
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Attendance
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not mandatory
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Evaluation methods
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Oral exam
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| Module:
(objectives)
TRAINING OBJECTIVES: The teaching will be oriented towards solving problems, analyzing and assessing risks, planning suitable prevention and protection interventions, paying attention to in-depth analysis based on the different levels of risk.
EXPECTED LEARNING RESULTS
1) Knowledge and understanding (knowledge and understanding): It will allow the acquisition of knowledge / skills to: - identify the dangers and assess the risks present in the workplace, including ergonomic and work-related stress risks; - identify the specific prevention and protection measures for the sector, including PPE, with reference to the specific nature of the risk and the work activity; - help identify adequate technical, organizational and procedural safety solutions for each type of risk. 2) Applying knowledge and understanding; possibility to apply knowledge in all work environments, with understanding of the technical and regulatory terms of workplace safety. Furthermore, ability to manage both training projects and technical assessments. 3) Autonomy of judgment (making judgments); Understanding if the technical and / or legislative settings have been carried out in a workmanlike manner within the company, and knowing how to manage the non-conformities present both from a technical and legal point of view. 4) Communication skills; Ability to relate also through the design of appropriate training courses. 5) Ability to learn (learning skills): verify learning also through work groups on specific topics.
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Language
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ITA |
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Type of certificate
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Profit certificate
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Credits
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4
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Contact Hours
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32
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Type of Activity
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Teacher
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Nobili Paolo
(syllabus)
Mathematical Optimization in aiding the design process. Problem definition and data collection. Formulation of the mathematical model. Determination of the solutions of the model. Model testing and validation. The linear programming model. The assumptions of linear programming. Examples and case studies. Integer and Mixed-Integer Programming. Some linear programming applications with binary variables. Innovative use of binary variables in model formulation. Solving integer programming problems. Nonlinear programming. Some applications of nonlinear programming. Formulation of models and their resolution using the "Lingo" software tool.
(reference books)
Python Crash Course - Eric Matthes - No Starch Press
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Dates of beginning and end of teaching activities
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From to |
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Delivery mode
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Traditional
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Attendance
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not mandatory
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Evaluation methods
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Oral exam
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